Tomography refers to a technique for capturing a two-dimensional (2D) or three-dimensional (3D) cross-sectional image of an object, through the use of radiation or any kind of penetrating wave. Computed Tomography (CT) refers to a medical imaging technique that uses X-rays and computer processors to collect and display 2D or 3D images or tomograms of an object. Magnetic Resonance imaging (MRI) refers to a tomographic technique that uses a powerful magnetic field and a radio frequency transmitter to capture detailed images of organs and structures inside the body.
Radiation therapy refers to a technique where cancer tumors are controlled or killed by the application of high energy ionizing radiation. In the case of external radiation therapy the ionizing radiation is applied from outside the body from one or more directions, which are all directed towards the tumor to be treated. The ionizing radiation is often generated by a linear electron accelerator. The uptake of radiation by a tissue volume is referred to as the dose given to the tissue. A complete cancer treatment usually consists of several radiation therapy sessions, each of which is referred to as a fraction.
Radiation treatment planning refers to the step preceding the radiotherapy sessions, during which the application of radiation is carefully planned. Different organs and tissues exhibit different sensitivity to radiation. Organs and tissue for which the radiation will cause most negative side effects are referred to as risk organs. The area containing the tumor to be treated is referred to as the target. During radiation treatment planning the goal is to provide a specific dose to the target, while keeping it as low as possible to the surrounding risk organs. The means available for this are the angles from which the radiation is applied, together with the shape and strength of the radiation beam. In order to achieve this, the radiation treatment planning step is typically preceded by a tomographic step, which is then used for the identification and localization of target and risk organs.
Attenuation refers to the gradual loss of energy as a signal passes through a medium. In the context of CT, attenuation of the X-ray energy occurs as the X-rays pass through different tissues and structures in the body. The grayscale values in the CT image constitute an accurate representation of this attenuation at each location. Different tissues have different properties and densities and, thus, produce different amounts of attenuation. The attenuation coefficient describes the extent to which a particular material or tissue causes a loss of energy. In the context of radiotherapy, attenuation occurs as the radiation passes through the body and dose is absorbed by different tissues and structures.
In order to be able to accurately calculate the dose given to both target and risk organs, it is of high importance to know the exact energy deposition at every location through which the radiation passes. For this reason the tomography preceding the radiation treatment planning is traditionally CT, since there is a relation between the CT values and the dose deposition of the high-energy radiation used for radiotherapy.
Since a CT image constitutes a representation of X-ray attenuation, the primary contrasts within a CT image is that between bone, soft-tissue and air. Both between and within different types of soft-tissues (such as organs, muscles and fat), the image contrast is highly limited. During radiation treatment planning, this low contrast is a disadvantage, since it limits the accuracy by which target and risk organs can be identified.
Traditionally, radiation therapy planning specialists must often estimate and guess at the target and risk organ size and location based on their experience. Bony structures, or marker implants, provide the primary reference landmarks within the image. For this reason, the usual practice during planning is to “overstate” the area within the patient for subsequent radiation treatment. Thus, the radiation beam will be sure to hit the intended target. However, the disadvantage is that otherwise healthy tissue is thereby also unnecessarily irradiated.
For this reason, modern radiotherapy often also includes an additional MRI scan which is also performed prior to the radiation treatment planning, which has superior contrast between different soft tissues compared to the CT image. Such MRI scan is typically aligned to the CT scan and used in conjunction with the CT during the radiation treatment planning.
However, even such combined CT/MRI workflow has several disadvantages. First, acquiring both an MRI and a CT is both expensive and time consuming, and it also adds additional discomfort to the patient. Secondly, the registration between MRI and CT is rarely perfect, which adds an uncertainty to the identification of both the target and the risk organs. In addition, the CT itself adds a significant radiation dose to the patient, which limits its repeated use in following tumor changes between fractions.
Therefore, a solution which would enable an MRI-only workflow, and thereby eliminate the requirement of CT, in radiation treatment planning, is highly sought for.
US 2011/0007959 discloses a method, wherein co-registered CT and MRI anatomical structure reference images are used. When an MR image of a patient is acquired, a user can click and drag landmarks on the reference MR image to deform the reference MR image to align with the patient MR image. The registration of landmarks also registers the patient MR image with a corresponding landmark in the co-registered reference CT image. However, this method requires extensive user interaction in order to generate desired electron density information.
In Hofmann et al, “MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration”, Journal of Nuclear Medicine, 2008, volume 49, issue 11, pages 1875-1883, a method for using MRI in creation of synthetic CT, or attenuation correction information, which accounts for radiation-attenuation properties of the tissue. The method uses a non-rigid registration algorithm for aligning a template MR image with a new subject's MR image. This alignment is then used to compute a desired result from a template CT image.